{
  "id": "cond-mat/9811109",
  "version": "v1",
  "published": "1998-11-08T14:53:29.000Z",
  "updated": "1998-11-08T14:53:29.000Z",
  "title": "Long-term properties of time series generated by a perceptron with various transfer functions",
  "authors": [
    "A. Priel",
    "I. Kanter"
  ],
  "comment": "9 two-columns Latex pages including 8 figures. Submitted to Physical Review E. For full quality figures, see http://faculty.biu.ac.il/~priel",
  "doi": "10.1103/PhysRevE.59.3368",
  "categories": [
    "cond-mat.dis-nn",
    "chao-dyn",
    "nlin.CD"
  ],
  "abstract": "We study the effect of various transfer functions on the properties of a time series generated by a continuous-valued feed-forward network in which the next input vector is determined from past output values. The parameter space for monotonic and non-monotonic transfer functions is analyzed in the unstable regions with the following main finding; non-monotonic functions can produce robust chaos whereas monotonic functions generate fragile chaos only. In the case of non-monotonic functions, the number of positive Lyapunov exponents increases as a function of one of the free parameters in the model, hence, high dimensional chaotic attractors can be generated. We extend the analysis to a combination of monotonic and non-monotonic functions.",
  "revisions": [
    {
      "version": "v1",
      "updated": "1998-11-08T14:53:29.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "time series",
      "long-term properties",
      "non-monotonic functions",
      "monotonic functions generate fragile chaos",
      "high dimensional chaotic attractors"
    ],
    "tags": [
      "journal article"
    ],
    "publication": {
      "publisher": "APS",
      "journal": "Phys. Rev. E"
    },
    "note": {
      "typesetting": "LaTeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}